Research Details
Evaluating the Suitability of GSMaP Satellite-Based Precipitation Data for Runoff Estimation in the Abra River Basin
Ma. Gloann Leizel P. Longboy, Christopher T. Zamuco, Nathaniel R. Alibuyog, Rodel T. Utrera
Category
Study
Status
Completed
Duration
Dec 27, 2022 -
Jun 26, 2025
Parent Project
→ Assessment, Monitoring, and Prediction of Coastal Flooding of Selected Municipalities in Region IRelated Studies
- • Storm Surge Modeling with DELFT-3D: The influence of Tide and Wind During Typhoon Ineng in the Laoag River Coastal Zone
- • Integrated Assessment of Tidal and Flood Control Scenarios on Inundation Using HECRAS
- • Integrated Assessment of Tidal and Flood Control Scenarios on Inundation Using HEC-HMS-RAS
- • Development of a Web-Based Platform for Integrated Coastal Monitoring and Flood Preparedness
- • Predictive Ability of Delft3D-Based Storm Surge Forecasts Using Historical and Forecasted Typhoon Tracks
- • Integrated assessment of tidal and flood control scenarios on inundation using HEC-RAS and HEC-HMS
Brief Description
This research assessed the viability of using GSMaP satellite precipitation data instead of traditional rain gauge measurements for flood prediction modeling in the Abra River Basin, Philippines. The study developed a comprehensive hydrological simulation using HEC-HMS software to determine whether satellite-based rainfall data could reliably estimate water runoff in regions with limited ground-based monitoring infrastructure. Researchers integrated satellite precipitation measurements with detailed watershed characteristics including topography, land use, and soil properties to create predictive models for flood forecasting and water resource management.
Expected Output
This study demonstrated that GSMaP satellite precipitation data can serve as an effective substitute for traditional rainfall monitoring in hydrological modeling applications within the Abra River Basin, Philippines. Using HEC-HMS software, researchers successfully developed a watershed simulation model that achieved 94% accuracy during calibration with Typhoon Mangkhut (2018) data, though performance decreased to 61% during validation with Typhoon Marce (2008) due to systematic underestimation of extreme rainfall events. The research establishes that satellite-based precipitation products provide a practical solution for flood forecasting and water management in data-scarce tropical regions, while identifying the need for bias correction techniques to improve accuracy during severe weather conditions. This framework offers a valuable methodology for implementing hydrological modeling in areas where conventional rainfall monitoring infrastructure is inadequate or unavailable.